Design, study, modelling and control of a new single-phase high power factor rectifier based on the single-ended primary inductance converter and the Sheppard–Taylor topology
Bibliographic record
Abstract
A new single-phase power factor corrector (PFC) based on the Sheppard–Taylor topology is studied. Compared with conventional PFCs, this topology facilitates a better input current tracking, lower voltage stresses across the devices and larger output voltage range for the same operating area. The converter is integrated as a PFC at the DC-end of a single-phase diode bridge. Pulse-width-modulated (PWM) multi-loops control schemes are proposed and developed in order to ensure a unity power factor at the AC-source side and a regulated voltage at the DC-load side. The first control method uses the simple and robust hysteretic-based controller; the second employs a conventional PI regulator; and the third is based on the model nonlinearity compensation approach. The design of the last two control methods is based on the knowledge of a mathematical model that would accurately represent the converter. This model is developed in this paper using the state-space averaging technique, and then the small-signal transfer functions of the converter are derived for linear control design purpose. The performance of the different control strategies is evaluated through simulation experiments carried out on a numerical version of the converter. The implemented model of the converter is obtained by using the switching function technique. The control system is tested under both rated and disturbed operating conditions. The system performance is evaluated in terms of source current total harmonic distortion (THD), input power factor, DC voltage stabilization, and regulation following load variations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".